DEGREE PROGRAMMES

: DATA MANAGEMENT AND ANALYSIS

General Description

History

Qualification Awarded

Level of Qualification

Specific Admission Requirements

Specific Arrangements for Recognition of Prior Learning (Formal, Non-Formal and Informal)

Qualification Requirements and Regulations

Profile of the Programme

Key Learning Outcomes

1   To be able to find and improve appropriate means and tools to collect data properly.
2   To be able to summarize data and generate information in order to help decision making.
3   To be able to make basic and advanced statistical analyses.
4   To be able to process stored data to generate information.
5   To be able to define business and financial decisions.
6   To be able to model business problems and to find and infer solutions based on these models.
7   To be able to formulate prudential business decisions and to compare alternatives.
8   To be able to visualize and present data properly and meaningfully.
9   To be able to use current information technologies for data management and analysis.
10   To be able to effectively use information technologies, statistics and operations research tools and techniques in sync.

Occupational Profiles of Graduates with Examples

Access to Further Studies

Course Structure Diagram with Credits


T: Theoretical P: Practice L: Laboratory
B: Spring Semester G: Fall Semester H: Full Year
1 .Semester:
Semester No Course Unit Code Course Unit Title Type of Course T P L ECTS
G 1 SBE 5000 TECHNIQUES OF SCIENTIFIC RESEARCH AND PUBLICATION ETHICS COMPULSORY 3 0 0 5
G 2 VYA 5005 DATABASE MANAGEMENT SYSTEMS AND DATA MAPPING COMPULSORY 3 0 0 5
G 3 VYA 5003 SURVEY RESEARCH AND METHODOLOGY COMPULSORY 3 0 0 5
G 4 VYA 5001 APPLIED STATISTICS COMPULSORY 3 0 0 5
G 0 - ELECTIVE COURSE ELECTIVE - - - 10
TOTAL:   30
 
1 .Semester Elective:
Semester No Course Unit Code Course Unit Title Type of Course T P L ECTS
G 1 VYA 5007 OPTIMIZATION AND SCENARIO ANALYSIS ELECTIVE 5 0 0 5
G 2 VYA 5011 MULTICRITERIA DECISION MAKING ELECTIVE 3 0 0 5
G 3 VYA 5009 COMPUTER TECHNOLOGIES AND PROGRAMMING ELECTIVE 3 0 0 5
 
2 .Semester:
Semester No Course Unit Code Course Unit Title Type of Course T P L ECTS
B 1 VYA 5002 APPLIED MULTIVARIATE ANALYSIS COMPULSORY 3 0 0 6
B 2 VYA 5014 FINANCIAL DATA ANALYSIS AND FORECASTING COMPULSORY 3 0 0 5
B 3 VYA 5096 SEMINAR COMPULSORY 0 2 0 2
B 4 VYA 5098 FIELD STUDY COMPULSORY 2 0 0 2
B 5 VYA 5006 DATA VISUALISATION AND REPORTING COMPULSORY 3 0 0 5
B 0 - ELECTIVE COURSE ELECTIVE - - - 10
TOTAL:   30
 
2 .Semester Elective:
Semester No Course Unit Code Course Unit Title Type of Course T P L ECTS
B 1 VYA 5008 SPATIAL STATISTICS AND ANALYSIS ELECTIVE 3 0 0 5
B 2 VYA 5012 PROCESS AND PERFORMANCE ANALYSIS ELECTIVE 3 0 0 5
B 3 VYA 5010 DATA MINING APPLICATIONS ELECTIVE 3 0 0 5
 
3.Semester:
Semester No Course Unit Code Course Unit Title Type of Course T P L ECTS
G 1 VYA 5099 THESIS COMPULSORY 0 1 0 30
TOTAL:   30
 
4.Semester:
Semester No Course Unit Code Course Unit Title Type of Course T P L ECTS
B 1 VYA 5099 THESIS COMPULSORY 0 1 0 30
TOTAL:   30
 

Examination Regulations, Assessment and Grading

Graduation Requirements

Mode of Study (Full-Time, Part-Time, E-Learning )

Programme Director or Equivalent